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1 March 2013, Computational Social Choice Seminar, Olivier Cailloux

Speaker: Olivier Cailloux (ILLC)

Title: Preference Modeling in Multiple Criteria Decision Aiding

Date: Friday 1 March 2013

Time: 16:00

Location: Room D1.113, Science Park 904, Amsterdam

I will briefly describe some typical goals of the
multiple criteria decision aiding (MCDA) research field related to
preference modeling, and as an example I will describe how this can be
applied to the multicriteria portfolio selection problem.

MCDA is interested in situations where multiple points of view
(criteria) may be used to rate objects (alternatives). We want to come
up with an aggregated output, for example, a quality label for each
alternative. When facing conflicting criteria, this requires a
subjective appreciation of how the criteria interact.

Preference modeling is the activity which aims at building a model of
the relation between the scores of evaluated alternatives on the
criteria and the aggregated output. This models the preferences of a
given individual (decision maker). The usual approach assumes that this
relation is well-defined in the decision maker's mind, whereas MCDA, on
the contrary, assumes that the decision maker can only talk about some
imprecise constraints on the set of such possible relations. It is even
possible that the constraints are in conflict. MCDA aims at coming up
with methods to help individuals solve these conflicts and satisfy as
much as possible their preferences.

As an example of what this different assumption permits, I will present
an MCDA method to solve a multicriteria portfolio selection problem.
Imagine a decision maker must establish a procedure to select a subset
of persons according to their performance on a set of criteria (think
about entrance examinations). The decision maker may like both the ideas
of affirmative action (making sure the procedure benefits some usually
underrepresented group) and of the non-discrimination principle (treat
everybody equally). We will see how the proposed MCDA method can be used
to help a decision maker ponder these two principles.